World bank about the ethiopian education system pdf download

Gross Domestic Product for Ethiopia. Literacy Rate, Adult Total for Ethiopia. Number of Bank Branches for Ethiopia. Number per , adults, Annual, Not Seasonally Adjusted to Bank Credit to Bank Deposits for Ethiopia. Index, Annual, Not Seasonally Adjusted to Internet users for Ethiopia.

Infant Mortality Rate for Ethiopia. Population ages 65 and above for Ethiopia. Bank Lending Deposit Spread for Ethiopia. Crude Birth Rate for Ethiopia. Population, Total for Ethiopia. Persons, Not Seasonally Adjusted. This book lays no claim to uncovering the full range of problems confronting education elsewhere.

It shows, however, the great importance attached to education in a variety of contexts, all of which are marked by dramatic social changes that place heavy demands upon the schools. How can studies in comparative. Case Studies in War-to-peace Transition. Authors: Nat J. Colletta, Markus Kostner, Ingo Wiederhofer. Before investing in and deploying EdTech, policymakers must ask what education challenges need to be addressed and what resulting change is desired.

Policies must be holistic to account for teacher capacity and incentives, appropriate digital learning resources linked to the curriculum, and formative assessments that capture learning.

Education at its core is a human-centered socially intensive endeavor. Technology is a means to these goals.

Design for scale begins with proactive engagement and empathy for all possible end-users -- students, teachers, administrators, parents, etc.

Engagement with different users will reveal different needs. Understanding these needs will lead to inclusive and flexible designs that will be equitable and hence scalable.

Today, the use of EdTech has demonstrated and is exacerbating inequities in education systems. This need not be the case. Beginning the design process with how technology can be utilized for all will lead to initiatives that are equitable and adaptable to specific contexts and thereby sustainable at scale. EdTech cannot replace teachers, it can only augment teaching. Evidence from around the world shows that, over time, the role of teachers become more central, and not peripheral, as the result of the effective use of EdTech.

Technology will replace some of what teachers currently do, while at the same time supporting teachers as they take on new, often more sophisticated duties and responsibilities as a result of technological change.

Teachers can be facilitators of learning, part of a learning team, a collaborator with outside expert mentors, a team leader on a project-based learning activity, etc. At the same time, in those circumstances where there is a scarcity of teachers or low-capacity teachers, technology can play an important role in assisting learners to, in part, overcome this absence. Where teachers lack content or pedagogical knowledge, technology can support structured lesson plans or text-based nudges to build this capacity.

Ministries of Education should leverage all stakeholders in the education system when developing and implementing EdTech programs and policies. The best content, software, applications, algorithms and edutainment will be spread across many innovators in the country and around the world. Ministries of Education should actively identify ways to find, incentive, integrate and sustain the creators in their country. This content can be delivered over the most appropriate channel — radio, TV, mobile, web — and bundled with data on learning and feedback to support continuous learning.

This ecosystem includes key stakeholders such as students, teachers, school leaders, parents, NGOs, donors and the private sector including app developers, publishers, equipment manufacturers, telecommunication companies and cloud service providers.

Technology can and should be used to easily collect data from educational institutions, analyze this data and support decision making. Technology is currently available to measure outcomes, track student performance, manage student retention, track book distribution, manage teacher recruitment, track education system spending, etc. Without these, countries will not be as efficient in supporting schools, students and teachers. This data however is diffused through various systems in Ministries of Education and other parts of government.

To operationalize this principle, Ministries of Education should promote transparent standards that facilitate interoperability of systems, data and content and remove barriers to competition in order to promote a data-driven decision-making culture. Many times, learnings from this data is not fed back into the system. With the pace of technological change, evidence quickly becomes stale.

The culture of data-driven decision making must be strengthened. In order to operationalize these principles, the World Bank focuses on the discovery, diffusion and deployment of new technologies. Discover, document, generate and analyze evidence-based technology solutions in education attuned to developing countries. The World Bank supports the EdTech community across countries to discover new innovations, build the evidence base and facilitate the transformation of ministries of education into learning organizations.

In some sense, policy makers are supported to think like a system, but act like entrepreneurs. Diffuse this knowledge widely across policy makers in our client countries and support capacity development to better use this new knowledge.

Due to this fact this study will try to pick out what are considered to be major factors in explaining the performance of the Ethiopian economy namely, labor, human capital, and physical capital, term of trade, foreign aid and export. As we discussed in the theoretical literature review, origin of the econometric model is extended neoclassical growth model.

Studies like Patrick Enuet al. Moreover, the variables are preferred based on their relevance and data availabilities. Therefore the mathematically relationship between real GDP and its major macroeconomic determinant are expressed as follows. So it can be transformed in to logarithm function. To test the long run relationship between dependent variable real GDP and independent variable labor, physical capital, human capital, and term of trade, foreign aid and Export ; the study will first investigate the time series properties of our data by using Augmented Dickey- Fuller ADF tests by checking the stationarity of the variables under unit root test.

Determinants Description Real GDP Yt :-Real gross domestic product GDP is an inflation-adjusted measure that reflects the value of all goods and services produced by an economy in a given year, expressed in base-year prices, and is often referred to as "constant-price," "inflation-corrected" GDP or "constant dollar GDP.

GDP is a macroeconomic assessment that measures the value of the goods and services produced by an economic entity in a specific period, adjusted for inflation. GDP is derived by valuing all production by an economy using a specific year's average prices. Governments use GDP as a comparison tool to analyze an economy's purchasing power and growth over time.

This is done by looking at the economic output of two periods and valuing each period with the same average prices and comparing the two together. GDP is calculated using a base year and does not include inflation, it represents an economy's nominal GDP if that economy did not realize any price changes when compared to the base year.

The size of the labor force is used to determine the unemployment rate. Unemployment is an important issue addressed in the study of macroeconomics. A person is unemployed if he or she is willing and able to work, actively job searching, yet still unable to find a job.

Therefore, by definition, people who are voluntarily idle are not classified as unemployed because they are not actively searching for a job. Just those people who are not working but actively looking for a job are counted as unemployed. Sometimes people become tired of looking for a job or believe they won't be able to find one and they are called discouraged workers. The percentage of the unemployed in the labor force is called the unemployment rate.

It only counts as unemployed those who have actively looked for a job in the past four weeks. First, are those who are under 16 even if they are working. Second, are those who don't want or need to work. They might be retired, in school full-time, or taking care of family members. Third, are those who want to work but haven't looked in the past year. Most have a serious health issue, like cancer.

They will go back to work once they recover. Fourth, are those who have looked in the past year, but not in the last four weeks. Physical Capital Kt :- Physical capital is one of the three main factors of production in economic theory. It consists of manmade goods that assist in the production process, like machinery, office supplies, transportation and computers.

In economics, physical capital or just capital is a factor of production or input into the process of production , consisting of machinery, buildings, computers, and the like. The others are natural resources including land , and labor—the stock of competences embodied in the labor force. Usually the value of land is not included in physical capital as it is not a reproducible product of human activity.

Therefore in this study, gross capital accumulation was used as proxy of this variable and have been expected a positive impact on economic growth. Human capital Ht :-Human capital is a term popularized by Gary Becker, an economist from the University of Chicago, and Jacob Mincer that refers to the stock of knowledge, habits, social and personality attributes, including creativity, embodied in the ability to perform labor so as to produce economic value.

Human capital is available to generate material wealth for an economy or a private firm. In a public organization, human capital is available as a resource to provide for the public welfare. How human capital is developed and managed may be one of the most important determinants of economic and organizational performance.

Human capital, intangible collective resources possessed by individuals and groups within a given population. These resources include all the knowledge, talents, skills, abilities, experience, intelligence, training, judgment, and wisdom possessed individually and collectively, the cumulative total of which represents a form of wealth available to nations and organizations to accomplish their goals.

Therefore this study has been used expenditure for education as a proxy of human capital and the sign of the coefficient would be expected positive. Term of Trade Tt :-Terms of trade TOT refers to the relative price of imports in terms of exports and is defined as the ratio of export prices to import prices.

It can be interpreted as the amount of import goods an economy can purchase per unit of export goods. The terms of trade may be influenced by the exchange rate because a rise in the value of a country's currency lowers the domestic prices of its imports but may not directly affect the prices of the commodities it exports.

If a country can buy more imports with a given quantity of exports, its terms of trade have improved. For example, during the commodity price boom, many resource-exporting developing countries experienced increases in their terms of trade.

In other words, for the same physical quantity of exports copper, rubber, oil etc. If import prices rise faster than export prices, the terms of trade have deteriorated. A greater volume of exports has to be sold to finance a given amount of imported goods and services.

Foreign Aid Ft :- Foreign aid is money that one country voluntarily transfers to another, which can take the form of a gift, a grant or a loan. In the United States, the term usually refers only to military and economic assistance the federal government gives to other governments. Broader definitions of aid include money transferred across borders by religious organizations, non-government organizations NGOs and foundations. Some have argued that remissions should be included, but they are rarely assumed to constitute aid.

Export Ext :-An export is a function of international trade whereby goods produced in one country are shipped to another country for future sale or trade.

The sale of such goods adds to the producing nation's gross output. If used for trade, exports are exchanged for other products or services in other countries. Exports are one of the oldest forms of economic transfer and occur on a large scale between nations that have fewer restrictions on trade, such as tariffs or subsidies. Most of the largest companies operating in advanced economies derive a substantial portion of their annual revenues from exports to other countries. The ability to export goods helps an economy to grow, by selling more overall goods and services.

The expected sign of this variable is expected to be positive. Descriptive and Econometric analysis 4. Over view of Ethiopian economy In this section, the research attempt to present an overview of the Ethiopian Economy with a focus on the economic structure and trends real GDP, physical capital, human capital, labor force and foreign aid.

The Ethiopian economy has continued to register high overall economic growth in the first year of implementation of the GTP. This sustainable growth rate of real GDP explains the availability of prudent macro economy and sectorial policies and implies that Ethiopia will achieve MDG targets. The growth rates of the GDP by major economic classification during the period under review indicates that agriculture, industry and services have registered growth rates of 9 percent, 15 percent and Ethiopia has consistently outperformed most in Africa and other countries and expanded much faster than the continent.

At the same time, the country still faces some structural weakness that present significant challenge in the medium term. The available evidence indicates that the rate of economic growth over the last three decades has been unsatisfactory. Regardless of the policy regimes, real total GDP grew on average by 3.

During , the country has registered After a decade of continuous expansion during which real GDP growth averaged Trends in Ethiopian Physical Capital Growth As described in the description of determinants, physical capital has major contribution for economic growth.

This physical capital can be measured as accumulation of capitals for that country. The growth rate for physical capital from , , and , is 2.

This paper tries to show physical capital by using graphical representation. Trends of Ethiopian physical capital Growth in Millions of birr from kt 0 year Source: - Data from CSA 4.

Trends in Ethiopian Human Capital Growth Most of the time expenditures both recurrent and capital of health, education and training were employed to measure human capital, which is the major driving force of economic growth. But this paper focused on government expenditure for education purpose. The total budget allocated to education in was Parallel to fast growing in human capital expenditure, economic growth was also robust and registered 8 percent annual growth during the same period Trends in Ethiopian Labor force Growth Whether they are subsistence farmers, salaried workers, or self-employed entrepreneurs, poor people derive most of their income from work.

This basic fact means that the level of employment, the quality of jobs, and the access which the poor have to decent earnings opportunities will be crucial determinants of poverty reduction. The intuition that jobs matter for development has not been lost on the governments of low income countries and the vast majority of national development strategies look to employment generation as a major channel for poverty reduction Katy Hull: Aid was served for consumption of the society rather than financing economic developments.

However, Aid ratio to real GDP decrease to 4. Figure 4. Econometric Analysis Many economic time series have common tendency of growing over time. In many cases, time series processes appear to be correlated simply because they all are tending over time for seasons related to observable factors. Ignoring this fact may lead one to falsely conclude that changes in one variable are caused by other variables Wooldridge: Models based on time series data are used for forecasting.

But its validity depends on the stationary of time series variables. Therefore, researches employing a time series data must be subject to stationary tests. Most economic time series variables are non-stationary unless differenced.

Therefore, one solution for the problem of non-stationary is to use the difference of variables. Unit Root Test A standard classical method of estimation that are used in the applied time series economics work are based on a set of assumptions and one of which is the stationary of the time series variables.

A time series data is saied to be stationary if its mean and variance are constant over time and the value of covariance between time periods depends only on the disturbance or lag between the two periods and not the actual time at which the covariance is computed Gujarati, Time series data are rarely stationary in level forms.

If a time series is not stationary in the sense just defined it is called a non-stationary time series. In other words, a non-stationary time series will have a time varying mean and variance or both. Here, the ADF test is employed to test for the unit root the null hypothesis that says variables are non-stationary against the alternative hypothesis the variable have no unit root.

If the result shows that variables are non-stationary at a level, or I 0. The second option is to check for stationary test in differences-first difference, second difference etc.

If the result shows the presence of non-stationary in the data, we deal with the problem by taking the first difference of the variables in the model as their first difference may be stationary.

If the result is stationary, then the variables are Saied to be integrated of order one, or I 1. Similarly, if the original series has to be integrated twice i.

In this study the variables of the model are tested for unit roots using ADF-test which augments DF test by lags of the dependent variable. The ADF test involves testing the null hypothesis of non-stationery of the variables against the alternative hypothesis of stationary. The logs of the dependent and independent variables in this study were tested for stationary.

All of them except gross domestic product Lnyt and term of trade Lntt are non-stationary at a level I 0. Then they were tested at first difference in which the results showed stationary in all variables. The results of the ADF test for each of the variables at level and at first difference are given below.

Table 4. But all of them except gross domestic product Lnyt and term of trade Lntt are non-stationary. But all the variables are stationary of order one, or I 1. As seen from table 4. The p-value of all the variables are less than 0. This implies that the null hypothesis cannot be accepted for all the variables in the logs. Thus the first difference of the variables are integrated of order one, or I 1.

The result from the test suggest that all the variables are I 1 indicating that the variables are stationary at 1st difference.

Another decision rule here is the t-statistics. The more negative the calculated t-value, the more the null hypothesis the existence of non-stationary is rejected and that of the alternative hypothesis variables are stationary is accepted. Multicollinearity Test Multicollinearity refers to a situation where a number of independent variables in a multiple regression model are closely correlated to one another.

Multicollinearity occurs when two or more predictors in the model are correlated and provide redundant information about the response. Multicollinearity can lead to skewed or misleading results when a researcher or analyst is attempting to determine how well each one of a number of individual independent variables can most effectively be utilized to predict or understand the dependent variable in a statistical model. In general, multicollinearity can lead to wider confidence intervals and less reliable probability values P values for the independent variables.

The existence of the problem of multicolleniarity is tested using correlation coefficient test and variance inflation factor VIF. Correlation above 0. Furthermore VIF above 10 shows the existence of multicolleniarity Guajarati, Remedial for multicollinearity test: - There are two methods for solving multicollinearity problems.

Thus are; do nothing or follow some rule of thumb. For simplicity, rule of thumb is used in this paper. Therefore to solve these problems, first difference in logarithm form is involved. Heteroscadesticity Test The existence of heteroscedasticity is a major concern in the application of regression analysis, including the analysis of variance, as it can invalidate statistical tests of significance that assume that the modeling errors are uncorrelated and uniform; hence that their variances do not vary with the effects being modeled.

Heteroscadesticity relates the distribution of the disturbance term, when the distribution of the error term is not the same for varies observations i. If the value of probability p is less than 0. But if the value of p is greater than 0. In this research the results in stata calcuation during testing of the heteroscadesticity problem the value of p is 0. Therefore, the regresors have constant variance, implying that homoscadestocity of the variables.

Co-Integration Test Time series variables may be non-stationary at a level, but their linear combination might be stationary. That is, co-integration means that despite being individually non-stationary, a linear combination of two or more time series can be stationary Gujarati: And also, if the residual found to be stationary of the same order, it can be said that the time series variables are co-integrated; implying a long run relationship.

It has been noticed that the presence of non- stationary in the variables at a level. The best way is to make variables stationary is by taking the first difference; however, valuable long run relationships among the variables would be lost after differencing. The test that employed for co-integration is the Engle-Granger test.

This test helps to check whether there is long run relationship or not. After, applying the unit root test test for non- stationary , the task that follows is to test for long run relationship. The long run relationship exists if and only if the variables are co-integrated i.